{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from psikit import Psikit\n",
    "from IPython.display import Image, display_png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "pk = Psikit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "pk.read_from_smiles(\"c1ccccc1\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimizer: Optimization complete!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-230.71352354216"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pk.optimize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pk.save_cube()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "find_vmd\n",
      "Parameters:\n",
      "  Cubefile Directory   .\n",
      "  Font size            20\n",
      "  Gzip Cube Files      False\n",
      "  Image height         500\n",
      "  Image width          500\n",
      "  Interactive Mode     False\n",
      "  Isosurface Color(s)  [3, 23]\n",
      "  Isosurface Value(s)  [0.05, -0.05]\n",
      "  Label MOs            True\n",
      "  Montage              True\n",
      "  Opacity              1.0\n",
      "  X-axis Rotation      30.0\n",
      "  Y-axis Rotation      40.0\n",
      "  Z-axis Rotation      15.0\n",
      "  Scaling Factor       1.0\n",
      "  X-axis Translation   0.0\n",
      "  Y-axis Translation   0.0\n",
      "  Z-axis Translation   0.0\n",
      "  VMD Path             /Applications/VMD1.9.4.app/Contents/vmd/vmd_MACOSXX86\n",
      "read options\n",
      "setup done\n",
      "cube done\n",
      "Plotting Psi_a_100_100-A.cube with isosurface values [0.0529853, -0.0529793]\n",
      "Plotting Psi_a_101_101-A.cube with isosurface values [0.0646591, -0.0646653]\n",
      "Plotting Psi_a_102_102-A.cube with isosurface values [0.0527656, -0.0527723]\n",
      "Plotting Psi_a_103_103-A.cube with isosurface values [0.0435506, -0.0435516]\n",
      "Plotting Psi_a_104_104-A.cube with isosurface values [0.0439361, -0.0439659]\n",
      "Plotting Psi_a_105_105-A.cube with isosurface values [0.0546034, -0.0546044]\n",
      "Plotting Psi_a_106_106-A.cube with isosurface values [0.0600706, -0.0600712]\n",
      "Plotting Psi_a_107_107-A.cube with isosurface values [0.0380527, -0.0380539]\n",
      "Plotting Psi_a_108_108-A.cube with isosurface values [0.0471048, -0.0470534]\n",
      "Plotting Psi_a_109_109-A.cube with isosurface values [0.0546187, -0.0546171]\n",
      "Plotting Psi_a_10_10-A.cube with isosurface values [0.0404385, -0.0404382]\n",
      "Plotting Psi_a_110_110-A.cube with isosurface values [0.0526063, -0.0526048]\n",
      "Plotting Psi_a_111_111-A.cube with isosurface values [0.0560259, -0.0560205]\n",
      "Plotting Psi_a_112_112-A.cube with isosurface values [0.0535457, -0.0535405]\n",
      "Plotting Psi_a_113_113-A.cube with isosurface values [0.0536658, -0.0536515]\n",
      "Plotting Psi_a_114_114-A.cube with isosurface values [0.0530359, -0.053055]\n",
      "Plotting Psi_a_115_115-A.cube with isosurface values [0.0416529, -0.0416623]\n",
      "Plotting Psi_a_116_116-A.cube with isosurface values [0.0404025, -0.0404031]\n",
      "Plotting Psi_a_117_117-A.cube with isosurface values [0.0447573, -0.0447494]\n",
      "Plotting Psi_a_118_118-A.cube with isosurface values [0.0435566, -0.0435481]\n",
      "Plotting Psi_a_119_119-A.cube with isosurface values [0.0462539, -0.0462196]\n",
      "Plotting Psi_a_11_11-A.cube with isosurface values [0.0404038, -0.0403994]\n",
      "Plotting Psi_a_120_120-A.cube with isosurface values [0.0461635, -0.0461516]\n",
      "Plotting Psi_a_12_12-A.cube with isosurface values [0.0334224, -0.033353]\n",
      "Plotting Psi_a_13_13-A.cube with isosurface values [0.0379054, -0.0379054]\n",
      "Plotting Psi_a_14_14-A.cube with isosurface values [0.0508558, -0.0508547]\n",
      "Plotting Psi_a_15_15-A.cube with isosurface values [0.0357363, -0.0357361]\n",
      "Plotting Psi_a_16_16-A.cube with isosurface values [0.0391251, -0.0391396]\n",
      "Plotting Psi_a_17_17-A.cube with isosurface values [0.0352166, -0.0352204]\n",
      "Plotting Psi_a_18_18-A.cube with isosurface values [0.0392106, -0.039208]\n",
      "Plotting Psi_a_19_19-A.cube with isosurface values [0.0408659, -0.040882]\n",
      "Plotting Psi_a_1_1-A.cube with isosurface values [0.28033, 0.0]\n",
      "Plotting Psi_a_20_20-A.cube with isosurface values [0.0360412, -0.0360367]\n",
      "Plotting Psi_a_21_21-A.cube with isosurface values [0.036461, -0.0364741]\n",
      "Plotting Psi_a_22_22-A.cube with isosurface values [0.0329912, -0.0329921]\n",
      "Plotting Psi_a_23_23-A.cube with isosurface values [0.0330877, -0.0330881]\n",
      "Plotting Psi_a_24_24-A.cube with isosurface values [0.0224977, -0.0224989]\n",
      "Plotting Psi_a_25_25-A.cube with isosurface values [0.0235961, -0.023596]\n",
      "Plotting Psi_a_26_26-A.cube with isosurface values [0.0240074, -0.0240074]\n",
      "Plotting Psi_a_27_27-A.cube with isosurface values [0.0233761, -0.0233829]\n",
      "Plotting Psi_a_28_28-A.cube with isosurface values [0.0244246, -0.0244241]\n",
      "Plotting Psi_a_29_29-A.cube with isosurface values [0.0240182, -0.0240184]\n",
      "Plotting Psi_a_2_2-A.cube with isosurface values [0.289922, -0.289918]\n",
      "Plotting Psi_a_30_30-A.cube with isosurface values [0.031347, -0.0313509]\n",
      "Plotting Psi_a_31_31-A.cube with isosurface values [0.0251724, -0.0251759]\n",
      "Plotting Psi_a_32_32-A.cube with isosurface values [0.0250444, -0.0250439]\n",
      "Plotting Psi_a_33_33-A.cube with isosurface values [0.0303727, -0.0303724]\n",
      "Plotting Psi_a_34_34-A.cube with isosurface values [0.0306925, -0.0306934]\n",
      "Plotting Psi_a_35_35-A.cube with isosurface values [0.0301311, -0.0301336]\n",
      "Plotting Psi_a_36_36-A.cube with isosurface values [0.031564, -0.0315457]\n",
      "Plotting Psi_a_37_37-A.cube with isosurface values [0.0288736, -0.0288735]\n",
      "Plotting Psi_a_38_38-A.cube with isosurface values [0.0297631, -0.0297685]\n",
      "Plotting Psi_a_39_39-A.cube with isosurface values [0.0269562, -0.0269527]\n",
      "Plotting Psi_a_3_3-A.cube with isosurface values [0.338179, -0.338176]\n",
      "Plotting Psi_a_40_40-A.cube with isosurface values [0.0248251, -0.0248248]\n",
      "Plotting Psi_a_41_41-A.cube with isosurface values [0.030073, -0.0300728]\n",
      "Plotting Psi_a_42_42-A.cube with isosurface values [0.0300686, -0.0300691]\n",
      "Plotting Psi_a_43_43-A.cube with isosurface values [0.0325552, -0.0325515]\n",
      "Plotting Psi_a_44_44-A.cube with isosurface values [0.0325553, -0.032558]\n",
      "Plotting Psi_a_45_45-A.cube with isosurface values [0.0315161, -0.0315217]\n",
      "Plotting Psi_a_46_46-A.cube with isosurface values [0.0294245, -0.0294298]\n",
      "Plotting Psi_a_47_47-A.cube with isosurface values [0.0286684, -0.0286684]\n",
      "Plotting Psi_a_48_48-A.cube with isosurface values [0.028968, -0.0289678]\n",
      "Plotting Psi_a_49_49-A.cube with isosurface values [0.0281508, -0.0281492]\n",
      "Plotting Psi_a_4_4-A.cube with isosurface values [0.29907, -0.289467]\n",
      "Plotting Psi_a_50_50-A.cube with isosurface values [0.0255125, -0.025512]\n",
      "Plotting Psi_a_51_51-A.cube with isosurface values [0.023336, -0.023336]\n",
      "Plotting Psi_a_52_52-A.cube with isosurface values [0.0234729, -0.023473]\n",
      "Plotting Psi_a_53_53-A.cube with isosurface values [0.0235727, -0.0235727]\n",
      "Plotting Psi_a_54_54-A.cube with isosurface values [0.0236941, -0.0236941]\n",
      "Plotting Psi_a_55_55-A.cube with isosurface values [0.021238, -0.0212395]\n",
      "Plotting Psi_a_56_56-A.cube with isosurface values [0.0265318, -0.0265317]\n",
      "Plotting Psi_a_57_57-A.cube with isosurface values [0.026403, -0.0264055]\n",
      "Plotting Psi_a_58_58-A.cube with isosurface values [0.0293796, -0.0293822]\n",
      "Plotting Psi_a_59_59-A.cube with isosurface values [0.0278522, -0.0278522]\n",
      "Plotting Psi_a_5_5-A.cube with isosurface values [0.342107, -0.335833]\n",
      "Plotting Psi_a_60_60-A.cube with isosurface values [0.0279467, -0.0279452]\n",
      "Plotting Psi_a_61_61-A.cube with isosurface values [0.0299558, -0.0299556]\n",
      "Plotting Psi_a_62_62-A.cube with isosurface values [0.0304382, -0.0304383]\n",
      "Plotting Psi_a_63_63-A.cube with isosurface values [0.0299731, -0.0299732]\n",
      "Plotting Psi_a_64_64-A.cube with isosurface values [0.063641, -0.0636315]\n",
      "Plotting Psi_a_65_65-A.cube with isosurface values [0.0516425, -0.0516627]\n",
      "Plotting Psi_a_66_66-A.cube with isosurface values [0.0526899, -0.0526737]\n",
      "Plotting Psi_a_67_67-A.cube with isosurface values [0.0553581, -0.0553531]\n",
      "Plotting Psi_a_68_68-A.cube with isosurface values [0.0276088, -0.0276111]\n",
      "Plotting Psi_a_69_69-A.cube with isosurface values [0.0291093, -0.0291048]\n",
      "Plotting Psi_a_6_6-A.cube with isosurface values [0.281277, -0.281279]\n",
      "Plotting Psi_a_70_70-A.cube with isosurface values [0.0537655, -0.0537729]\n",
      "Plotting Psi_a_71_71-A.cube with isosurface values [0.0552311, -0.0552725]\n",
      "Plotting Psi_a_72_72-A.cube with isosurface values [0.0435948, -0.0436224]\n",
      "Plotting Psi_a_73_73-A.cube with isosurface values [0.0328853, -0.0328849]\n",
      "Plotting Psi_a_74_74-A.cube with isosurface values [0.0430291, -0.043043]\n",
      "Plotting Psi_a_75_75-A.cube with isosurface values [0.0257321, -0.0257337]\n",
      "Plotting Psi_a_76_76-A.cube with isosurface values [0.0458547, -0.0458552]\n",
      "Plotting Psi_a_77_77-A.cube with isosurface values [0.0494258, -0.049419]\n",
      "Plotting Psi_a_78_78-A.cube with isosurface values [0.0400556, -0.040052]\n",
      "Plotting Psi_a_79_79-A.cube with isosurface values [0.0401515, -0.0401424]\n",
      "Plotting Psi_a_7_7-A.cube with isosurface values [0.0437048, -0.0426561]\n",
      "Plotting Psi_a_80_80-A.cube with isosurface values [0.0359129, -0.0359138]\n",
      "Plotting Psi_a_81_81-A.cube with isosurface values [0.0357842, -0.0357842]\n",
      "Plotting Psi_a_82_82-A.cube with isosurface values [0.0336639, -0.033663]\n",
      "Plotting Psi_a_83_83-A.cube with isosurface values [0.0388873, -0.0388891]\n",
      "Plotting Psi_a_84_84-A.cube with isosurface values [0.0382899, -0.0382862]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Psi_a_85_85-A.cube with isosurface values [0.0525889, -0.0525902]\n",
      "Plotting Psi_a_86_86-A.cube with isosurface values [0.0518022, -0.0517836]\n",
      "Plotting Psi_a_87_87-A.cube with isosurface values [0.0471893, -0.0471904]\n",
      "Plotting Psi_a_88_88-A.cube with isosurface values [0.0433201, -0.0433132]\n",
      "Plotting Psi_a_89_89-A.cube with isosurface values [0.0429296, -0.042935]\n",
      "Plotting Psi_a_8_8-A.cube with isosurface values [0.0419202, -0.0419122]\n",
      "Plotting Psi_a_90_90-A.cube with isosurface values [0.0486204, -0.0486207]\n",
      "Plotting Psi_a_91_91-A.cube with isosurface values [0.0498826, -0.0498727]\n",
      "Plotting Psi_a_92_92-A.cube with isosurface values [0.052563, -0.0525392]\n",
      "Plotting Psi_a_93_93-A.cube with isosurface values [0.0286104, -0.0286095]\n",
      "Plotting Psi_a_94_94-A.cube with isosurface values [0.0286184, -0.0286164]\n",
      "Plotting Psi_a_95_95-A.cube with isosurface values [0.0457728, -0.0458067]\n",
      "Plotting Psi_a_96_96-A.cube with isosurface values [0.0456521, -0.0456488]\n",
      "Plotting Psi_a_97_97-A.cube with isosurface values [0.0368242, -0.0368248]\n",
      "Plotting Psi_a_98_98-A.cube with isosurface values [0.0278935, -0.0278908]\n",
      "Plotting Psi_a_99_99-A.cube with isosurface values [0.0519307, -0.0519572]\n",
      "Plotting Psi_a_9_9-A.cube with isosurface values [0.0422579, -0.0422601]\n",
      "Plotting Psi_b_100_100-A.cube with isosurface values [0.0529853, -0.0529793]\n",
      "Plotting Psi_b_101_101-A.cube with isosurface values [0.0646591, -0.0646653]\n",
      "Plotting Psi_b_102_102-A.cube with isosurface values [0.0527656, -0.0527723]\n",
      "Plotting Psi_b_103_103-A.cube with isosurface values [0.0435506, -0.0435516]\n",
      "Plotting Psi_b_104_104-A.cube with isosurface values [0.0439361, -0.0439659]\n",
      "Plotting Psi_b_105_105-A.cube with isosurface values [0.0546034, -0.0546044]\n",
      "Plotting Psi_b_106_106-A.cube with isosurface values [0.0600706, -0.0600712]\n",
      "Plotting Psi_b_107_107-A.cube with isosurface values [0.0380527, -0.0380539]\n",
      "Plotting Psi_b_108_108-A.cube with isosurface values [0.0471048, -0.0470534]\n",
      "Plotting Psi_b_109_109-A.cube with isosurface values [0.0546187, -0.0546171]\n",
      "Plotting Psi_b_10_10-A.cube with isosurface values [0.0404385, -0.0404382]\n",
      "Plotting Psi_b_110_110-A.cube with isosurface values [0.0526063, -0.0526048]\n",
      "Plotting Psi_b_111_111-A.cube with isosurface values [0.0560259, -0.0560205]\n",
      "Plotting Psi_b_112_112-A.cube with isosurface values [0.0535457, -0.0535405]\n",
      "Plotting Psi_b_113_113-A.cube with isosurface values [0.0536658, -0.0536515]\n",
      "Plotting Psi_b_114_114-A.cube with isosurface values [0.0530359, -0.053055]\n",
      "Plotting Psi_b_115_115-A.cube with isosurface values [0.0416529, -0.0416623]\n",
      "Plotting Psi_b_116_116-A.cube with isosurface values [0.0404025, -0.0404031]\n",
      "Plotting Psi_b_117_117-A.cube with isosurface values [0.0447573, -0.0447494]\n",
      "Plotting Psi_b_118_118-A.cube with isosurface values [0.0435566, -0.0435481]\n",
      "Plotting Psi_b_119_119-A.cube with isosurface values [0.0462539, -0.0462196]\n",
      "Plotting Psi_b_11_11-A.cube with isosurface values [0.0404038, -0.0403994]\n",
      "Plotting Psi_b_120_120-A.cube with isosurface values [0.0461635, -0.0461516]\n",
      "Plotting Psi_b_12_12-A.cube with isosurface values [0.0334224, -0.033353]\n",
      "Plotting Psi_b_13_13-A.cube with isosurface values [0.0379054, -0.0379054]\n",
      "Plotting Psi_b_14_14-A.cube with isosurface values [0.0508558, -0.0508547]\n",
      "Plotting Psi_b_15_15-A.cube with isosurface values [0.0357363, -0.0357361]\n",
      "Plotting Psi_b_16_16-A.cube with isosurface values [0.0391251, -0.0391396]\n",
      "Plotting Psi_b_17_17-A.cube with isosurface values [0.0352166, -0.0352204]\n",
      "Plotting Psi_b_18_18-A.cube with isosurface values [0.0392106, -0.039208]\n",
      "Plotting Psi_b_19_19-A.cube with isosurface values [0.0408659, -0.040882]\n",
      "Plotting Psi_b_1_1-A.cube with isosurface values [0.28033, 0.0]\n",
      "Plotting Psi_b_20_20-A.cube with isosurface values [0.0360412, -0.0360367]\n",
      "Plotting Psi_b_21_21-A.cube with isosurface values [0.036461, -0.0364741]\n",
      "Plotting Psi_b_22_22-A.cube with isosurface values [0.0329912, -0.0329921]\n",
      "Plotting Psi_b_23_23-A.cube with isosurface values [0.0330877, -0.0330881]\n",
      "Plotting Psi_b_24_24-A.cube with isosurface values [0.0224977, -0.0224989]\n",
      "Plotting Psi_b_25_25-A.cube with isosurface values [0.0235961, -0.023596]\n",
      "Plotting Psi_b_26_26-A.cube with isosurface values [0.0240074, -0.0240074]\n",
      "Plotting Psi_b_27_27-A.cube with isosurface values [0.0233761, -0.0233829]\n",
      "Plotting Psi_b_28_28-A.cube with isosurface values [0.0244246, -0.0244241]\n",
      "Plotting Psi_b_29_29-A.cube with isosurface values [0.0240182, -0.0240184]\n",
      "Plotting Psi_b_2_2-A.cube with isosurface values [0.289922, -0.289918]\n",
      "Plotting Psi_b_30_30-A.cube with isosurface values [0.031347, -0.0313509]\n",
      "Plotting Psi_b_31_31-A.cube with isosurface values [0.0251724, -0.0251759]\n",
      "Plotting Psi_b_32_32-A.cube with isosurface values [0.0250444, -0.0250439]\n",
      "Plotting Psi_b_33_33-A.cube with isosurface values [0.0303727, -0.0303724]\n",
      "Plotting Psi_b_34_34-A.cube with isosurface values [0.0306925, -0.0306934]\n",
      "Plotting Psi_b_35_35-A.cube with isosurface values [0.0301311, -0.0301336]\n",
      "Plotting Psi_b_36_36-A.cube with isosurface values [0.031564, -0.0315457]\n",
      "Plotting Psi_b_37_37-A.cube with isosurface values [0.0288736, -0.0288735]\n",
      "Plotting Psi_b_38_38-A.cube with isosurface values [0.0297631, -0.0297685]\n",
      "Plotting Psi_b_39_39-A.cube with isosurface values [0.0269562, -0.0269527]\n",
      "Plotting Psi_b_3_3-A.cube with isosurface values [0.338179, -0.338176]\n",
      "Plotting Psi_b_40_40-A.cube with isosurface values [0.0248251, -0.0248248]\n",
      "Plotting Psi_b_41_41-A.cube with isosurface values [0.030073, -0.0300728]\n",
      "Plotting Psi_b_42_42-A.cube with isosurface values [0.0300686, -0.0300691]\n",
      "Plotting Psi_b_43_43-A.cube with isosurface values [0.0325552, -0.0325515]\n",
      "Plotting Psi_b_44_44-A.cube with isosurface values [0.0325553, -0.032558]\n",
      "Plotting Psi_b_45_45-A.cube with isosurface values [0.0315161, -0.0315217]\n",
      "Plotting Psi_b_46_46-A.cube with isosurface values [0.0294245, -0.0294298]\n",
      "Plotting Psi_b_47_47-A.cube with isosurface values [0.0286684, -0.0286684]\n",
      "Plotting Psi_b_48_48-A.cube with isosurface values [0.028968, -0.0289678]\n",
      "Plotting Psi_b_49_49-A.cube with isosurface values [0.0281508, -0.0281492]\n",
      "Plotting Psi_b_4_4-A.cube with isosurface values [0.29907, -0.289467]\n",
      "Plotting Psi_b_50_50-A.cube with isosurface values [0.0255125, -0.025512]\n",
      "Plotting Psi_b_51_51-A.cube with isosurface values [0.023336, -0.023336]\n",
      "Plotting Psi_b_52_52-A.cube with isosurface values [0.0234729, -0.023473]\n",
      "Plotting Psi_b_53_53-A.cube with isosurface values [0.0235727, -0.0235727]\n",
      "Plotting Psi_b_54_54-A.cube with isosurface values [0.0236941, -0.0236941]\n",
      "Plotting Psi_b_55_55-A.cube with isosurface values [0.021238, -0.0212395]\n",
      "Plotting Psi_b_56_56-A.cube with isosurface values [0.0265318, -0.0265317]\n",
      "Plotting Psi_b_57_57-A.cube with isosurface values [0.026403, -0.0264055]\n",
      "Plotting Psi_b_58_58-A.cube with isosurface values [0.0293796, -0.0293822]\n",
      "Plotting Psi_b_59_59-A.cube with isosurface values [0.0278522, -0.0278522]\n",
      "Plotting Psi_b_5_5-A.cube with isosurface values [0.342107, -0.335833]\n",
      "Plotting Psi_b_60_60-A.cube with isosurface values [0.0279467, -0.0279452]\n",
      "Plotting Psi_b_61_61-A.cube with isosurface values [0.0299558, -0.0299556]\n",
      "Plotting Psi_b_62_62-A.cube with isosurface values [0.0304382, -0.0304383]\n",
      "Plotting Psi_b_63_63-A.cube with isosurface values [0.0299731, -0.0299732]\n",
      "Plotting Psi_b_64_64-A.cube with isosurface values [0.063641, -0.0636315]\n",
      "Plotting Psi_b_65_65-A.cube with isosurface values [0.0516425, -0.0516627]\n",
      "Plotting Psi_b_66_66-A.cube with isosurface values [0.0526899, -0.0526737]\n",
      "Plotting Psi_b_67_67-A.cube with isosurface values [0.0553581, -0.0553531]\n",
      "Plotting Psi_b_68_68-A.cube with isosurface values [0.0276088, -0.0276111]\n",
      "Plotting Psi_b_69_69-A.cube with isosurface values [0.0291093, -0.0291048]\n",
      "Plotting Psi_b_6_6-A.cube with isosurface values [0.281277, -0.281279]\n",
      "Plotting Psi_b_70_70-A.cube with isosurface values [0.0537655, -0.0537729]\n",
      "Plotting Psi_b_71_71-A.cube with isosurface values [0.0552311, -0.0552725]\n",
      "Plotting Psi_b_72_72-A.cube with isosurface values [0.0435948, -0.0436224]\n",
      "Plotting Psi_b_73_73-A.cube with isosurface values [0.0328853, -0.0328849]\n",
      "Plotting Psi_b_74_74-A.cube with isosurface values [0.0430291, -0.043043]\n",
      "Plotting Psi_b_75_75-A.cube with isosurface values [0.0257321, -0.0257337]\n",
      "Plotting Psi_b_76_76-A.cube with isosurface values [0.0458547, -0.0458552]\n",
      "Plotting Psi_b_77_77-A.cube with isosurface values [0.0494258, -0.049419]\n",
      "Plotting Psi_b_78_78-A.cube with isosurface values [0.0400556, -0.040052]\n",
      "Plotting Psi_b_79_79-A.cube with isosurface values [0.0401515, -0.0401424]\n",
      "Plotting Psi_b_7_7-A.cube with isosurface values [0.0437048, -0.0426561]\n",
      "Plotting Psi_b_80_80-A.cube with isosurface values [0.0359129, -0.0359138]\n",
      "Plotting Psi_b_81_81-A.cube with isosurface values [0.0357842, -0.0357842]\n",
      "Plotting Psi_b_82_82-A.cube with isosurface values [0.0336639, -0.033663]\n",
      "Plotting Psi_b_83_83-A.cube with isosurface values [0.0388873, -0.0388891]\n",
      "Plotting Psi_b_84_84-A.cube with isosurface values [0.0382899, -0.0382862]\n",
      "Plotting Psi_b_85_85-A.cube with isosurface values [0.0525889, -0.0525902]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Plotting Psi_b_86_86-A.cube with isosurface values [0.0518022, -0.0517836]\n",
      "Plotting Psi_b_87_87-A.cube with isosurface values [0.0471893, -0.0471904]\n",
      "Plotting Psi_b_88_88-A.cube with isosurface values [0.0433201, -0.0433132]\n",
      "Plotting Psi_b_89_89-A.cube with isosurface values [0.0429296, -0.042935]\n",
      "Plotting Psi_b_8_8-A.cube with isosurface values [0.0419202, -0.0419122]\n",
      "Plotting Psi_b_90_90-A.cube with isosurface values [0.0486204, -0.0486207]\n",
      "Plotting Psi_b_91_91-A.cube with isosurface values [0.0498826, -0.0498727]\n",
      "Plotting Psi_b_92_92-A.cube with isosurface values [0.052563, -0.0525392]\n",
      "Plotting Psi_b_93_93-A.cube with isosurface values [0.0286104, -0.0286095]\n",
      "Plotting Psi_b_94_94-A.cube with isosurface values [0.0286184, -0.0286164]\n",
      "Plotting Psi_b_95_95-A.cube with isosurface values [0.0457728, -0.0458067]\n",
      "Plotting Psi_b_96_96-A.cube with isosurface values [0.0456521, -0.0456488]\n",
      "Plotting Psi_b_97_97-A.cube with isosurface values [0.0368242, -0.0368248]\n",
      "Plotting Psi_b_98_98-A.cube with isosurface values [0.0278935, -0.0278908]\n",
      "Plotting Psi_b_99_99-A.cube with isosurface values [0.0519307, -0.0519572]\n",
      "Plotting Psi_b_9_9-A.cube with isosurface values [0.0422579, -0.0422601]\n",
      "run vmd\n",
      "call montage\n",
      "zip\n"
     ]
    }
   ],
   "source": [
    "# https://github.com/fevangelista/vmd_cube\n",
    "!python vmd_cube.py --imagew=500 --imageh=500"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## tga2png\n",
    "\n",
    "    #!/usr/bin/env python\n",
    "    \n",
    "    from PIL import Image\n",
    "    import sys\n",
    "    \n",
    "    tgafile = sys.argv[1]\n",
    "    pngfile = tgafile.split(\".\")[0] + \".png\"\n",
    "    \n",
    "    im = Image.open(tgafile)\n",
    "    im.save(pngfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "!~/bin/tga2png Psi_a_21_21-A.tga"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display_png(Image(\"Psi_a_21_21-A.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
